Population calcium responses of Purkinje cells in the oculomotor cerebellum driven by non-visual input

The olivary input to the cerebellum dissociates sensory events from movement plans

Neurons in the inferior olive are thought to anatomically organize the Purkinje cells (P-cells) of the cerebellum into computational modules, but what is computed by each module? Here, we designed a saccade task in marmosets that dissociated sensory events from motor events and then recorded the complex and simple spikes of hundreds of P-cells. We found that when a visual target was presented at a random location, the olive reported the direction of that sensory event to one group of P-cells, but not to a second group. However, just before movement onset, it reported the direction of the planned movement to both groups, even if that movement was not toward the target. At the end of the movement if the subject experienced an error but chose to withhold the corrective movement, only the first group received information about the sensory prediction error. We organized the P-cells based on the information content of their olivary input and found that in the group that received sensory information, the simple spikes were suppressed during fixation, then produced a burst before saccade onset in a direction consistent with assisting the movement. In the second group, the simple spikes were not suppressed during fixation but burst near saccade deceleration in a direction consistent with stopping the movement. Thus, the olive differentiated the P-cells based on whether they would receive sensory or motor information, and this defined their contributions to control of movements as well as holding still.

Synaptic weight dynamics underlying systems consolidation of a memory

Systems consolidation is a common feature of learning and memory systems, in which a long-term memory initially stored in one brain region becomes persistently stored in another region. We studied the dynamics of systems consolidation in simple circuit architectures modeling core features of many memory systems: an early- and late-learning brain region and two sites of plasticity. We show that the synaptic dynamics of the circuit during consolidation of an analog memory can be understood as a temporal integration process, by which transient changes in activity driven by plasticity in the early-learning area are accumulated into persistent synaptic changes at the late-learning site. This simple principle leads to two constraints on the circuit operation for consolidation to be implemented successfully. First, the plasticity rule at the late-learning site must stably support a continuum of possible outputs for a given input. We show that this is readily achieved by heterosynaptic but not standard Hebbian rules, that it naturally leads to a speed-accuracy tradeoff in systems consolidation, and that it provides a concrete circuit instantiation for how systems consolidation solves the stability-plasticity dilemma. Second, to turn off the consolidation process and prevent erroneous changes at the late-learning site, neural activity in the early-learning area must be reset to its baseline activity. We propose two biologically plausible implementations for this reset that suggest novel roles for core elements of the cerebellar circuit.

Internal models of self-motion: neural computations by the vestibular cerebellum

The vestibular cerebellum plays an essential role in maintaining our balance and ensuring perceptual stability during activities of daily living. Here I examine three key regions of the vestibular cerebellum: the floccular lobe, anterior vermis (lobules I-V), and nodulus and ventral uvula (lobules X-IX of the posterior vermis). These cerebellar regions encode vestibular information and combine it with extravestibular signals to create internal models of eye, head, and body movements, as well as their spatial orientation with respect to gravity. To account for changes in the external environment and/or biomechanics during self-motion, the neural mechanisms underlying these computations are continually updated to ensure accurate motor behavior. To date, studies on the vestibular cerebellum have predominately focused on passive vestibular stimulation, whereas in actuality most stimulation is the result of voluntary movement. Accordingly, I also consider recent research exploring these computations during active self-motion and emerging evidence establishing the cerebellum's role in building predictive models of self-generated movement.

Molecular layer disinhibition unlocks climbing-fiber-instructed motor learning in the cerebellum

Climbing fibers supervise cerebellar learning by providing signals to Purkinje cells (PCs) that instruct adaptive changes to mistakenly performed movements. Yet, climbing fibers are regularly active, even during well performed movements, suggesting that a mechanism dynamically regulates the ability of climbing fibers to induce corrective plasticity in response to motor errors. We found that molecular layer interneurons (MLIs), whose inhibition of PCs powerfully opposes climbing-fiber-mediated excitation, serve this function. Optogenetically suppressing the activity of floccular MLIs in mice during the vestibulo-ocular reflex (VOR) induces a learned increase in gain despite the absence of performance errors. Suppressing MLIs when the VOR is mistakenly underperformed reveled that their inhibitory output is necessary to orchestrate gain-increase learning by conditionally permitting climbing fibers to instruct plasticity induction during ipsiversive head turns. Ablation of an MLI circuit for PC disinhibition prevents gain-increase learning during VOR performance errors which was rescued by re-imposing PC disinhibition through MLI activity suppression. Our findings point to a decisive role for MLIs in gating climbing-fiber-mediated learning through their context-dependent inhibition of PCs.

Effect of a differential training paradigm with varying frequencies and amplitudes on adaptation of vestibulo-ocular reflex in mice

The vestibulo-ocular reflex (VOR) functions to maintain eye stability during head movement, and VOR gain can be dynamically increased or decreased by gain-up or gain-down adaptation. In this study, we investigated the impact of a differential training paradigm with varying frequencies and amplitudes on the level of VOR adaptation in mice. Training for gain-up (out of phase) or gain-down (in phase) VOR adaptation was applied for 60 min using two protocols: (1) oscillation of a drum and turntable with fixed frequency and differing amplitudes (0.5 Hz/2.5°, 0.5 Hz/5° and 0.5 Hz/10°). (2) Oscillation of a drum and turntable with fixed amplitude and a differing frequency (0.25 Hz/5°, 0.5 Hz/5° and 1 Hz/5°). VOR adaptation occurred distinctively in gain-up and gain-down learning. In gain-up VOR adaptation, the learned increase in VOR gain was greatest when trained with the same frequency and amplitude as the test stimulation, and VOR gain decreased after gain-up training with too high a frequency or amplitude. In gain-down VOR adaptation, the decrease in VOR gain increased as the training frequency or amplitude increased. These results suggest that different mechanisms are, at least in part, involved in gain-up and gain-down VOR adaptation.